The Martian atmosphere (from the surface up to the outer layers) is a very dynamic system, quickly responding to strong radiative forcing coming from the absorption of solar radiation from dust particles lofted during dust storms. So far, such dynamical phenomena at short time scales and large spatial scales have been observed mainly from spacecraft in polar or quasi-polar orbits, which cannot provide continuous and simultaneous observations over fixed, large regions. This limitation can be bypassed using spacecraft in equatorial, circular, planet-synchronous (i.e. areostationary) orbit at an altitude of 17,031.5 km above the Martian surface. Besides their possible use as communication relays for ground-based assets, for space weather monitoring (they orbit outside Mars' bow shock), and for the study of surface properties (e.g. thermal inertia and albedo), the unique scientific advantages of areostationary satellites for weather monitoring are comparable to those provided by geostationary satellites. These platforms greatly increase the temporal resolution and coverage of single events, and are ideally suited for data assimilation in global climate models. Thanks to NASA PSDS3 program, we have elaborated a mission concept to put a low-cost, low-weight, ESPA-class SmallSat in areostationary orbit, which is capable of supporting various tank sizes in order to provide a wide range of ΔV for three different Mars arrival scenarios. ExoTerra Resource LLC adapted its "Electrically Propelled Interplanetary CubeSat" bus as part of the mission design. Despite the optimization of the flight trajectories and the use of machine learning algorithms to prioritize data downlink, the conclusions of the concept study clearly point towards the current challenges represented by propulsion, communication, and possibly radiation tolerance for scientific SmallSat missions to Mars. Such conclusions are generally common among all low-cost interplanetary SmallSat concepts. Furthermore, a single areostationary satellite is enough to provide a full-disk view to monitor regional dust storms and water ice clouds at specific locations, but cannot provide the global coverage required to understand extreme phenomena such as Martian planetary-scale dust events. For this reason, we have recently started to study a more advanced mission concept involving the use of at least three areostationary satellites. This new study is carried out in collaboration with the Jet Propulsion Laboratory within the scope of a wider NASA-funded project (PMCS program) looking at a constellation concept. The challenge is to keep the areostationary satellite configuration within the ESPA class limits, in order to take advantage of possible future rideshare opportunities.

We have used high-resolution digital terrain models (DTMs) of two rover landing sites based on mosaicked images from the High-Resolution Imaging Science Experiment (HiRISE) camera as a reference to evaluate DTMs based on High-Resolution Stereo Camera (HRSC) and Context Camera (CTX) images. The Next-Generation Automatic Terrain Extraction (NGATE) matcher in the SOCET SET and GXP® commercial photogrammetric systems produces DTMs with good (small) horizontal resolution but large vertical error. Somewhat surprisingly, results for NGATE are terrain dependent, with poorer resolution and smaller errors on smoother surfaces. Multiple approaches to smoothing the NGATE DTMs give similar tradeoffs between resolution and error; a 5 × 5 lowpass filter is near optimal in terms of both combined resolution-error performance and local slope estimation. Smoothing with an area-based matcher, the standard processing for U.S. Geological Survey planetary DTMs, yields similar errors to the 5 × 5 filter at slightly worse resolution. DTMs from the HRSC team processing pipeline fall within this same trade space but are less sensitive to terrain roughness. DTMs produced with the Ames Stereo Pipeline also fall in this space at resolutions intermediate between NGATE and the team pipeline. Considered individually, resolution and error each varied by approximately a factor of 2. Matching errors were 0.2–0.5 pixels but most results fell in the 0.2–0.3 pixel range that has been stated as a rule of thumb in multiple prior studies. Horizontal resolutions of 10–20 image pixels were found, consistently greater than the 3–5 pixel spacing generally used for stereo DTM production. Resolution and precision were inversely correlated; their product varied by ≤20% (4–5 pixels squared). Refinement of the stereo DTM by photoclinometry can yield quantitative improvement in resolution (more than a factor of 2), provided that albedo variations over distances smaller than the stereo DTM resolution are not too severe. We offer specific guidance for both producers and users of planetary stereo DTMs, based on our results.

We have used high-precision, high-resolution digital terrain models (DTMs) of the NASA Mars Science Laboratory and Mars 2020 rover landing sites based on mosaicked images from the Mars Reconnaissance Orbiter High Resolution Imaging Science Experiment (MRO HiRISE) camera as a reference data set to evaluate DTMs based on Mars Express High Resolution Stereo Camera (MEX HRSC) images. The Next Generation Automatic Terrain Extraction (NGATE) matcher in the SOCET SET/GXP® commercial photogram- metric system produces DTMs with relatively good (small) horizontal resolution but high error, and results are terrain dependent, with poorer resolution and smaller errors on smoother surfaces. Multiple approaches to smoothing the NGATE DTMs give very similar tradeoffs between resolution and error. Smoothing the NGATE DTMs with a 5x5 lowpass filter is near optimal in terms of both combined resolution-error performance and local slope estimation, but smoothing with a single pass of an area-based matcher, which has been the standard approach for generating planetary DTMs at the U.S. Geological Survey to date results in similar errors and only slightly worse resolution. DTMs from the HRSC team processing pipeline fall within this same trade space but are less sensitive to terrain roughness. DTMs produced with the Ames Stereo Pipeline also fall in this space at resolutions intermediate between NGATE and the team pipeline. Although DTM resolution and error each vary by a factor of 2, the product of resolution and error is much more consistent, varying by ≤20% across multiple image sets and matching algorithms. Refinement of the stereo DTM by photoclinometry can yield significant quantitative improvement in resolution and some improvement in error (improving their product by as much as a factor of 2), provided that albedo variations over distances smaller than the stereo DTM resolution are not too severe.

Jupiter’s moon Europa harbors one of the most likely environments for extant extraterrestrial life. Determining whether Europa is truly habitable requires understanding the structure and thickness of its ice shell, including the existence of perched water or brines. Stereo-derived topography from images acquired by NASA Galileo’s Solid State Imager (SSI) of Europa are often used as a constraint on ice shell structure and heat flow, but the uncertainty in such topography has, to date, not been rigorously assessed. To evaluate the current uncertainty in Europa’s topography we generated and compared digital terrain models (DTMs) of Europa from SSI images using both the open-source Ames Stereo Pipeline (ASP) software and the commercial SOCET SET® software. After first describing the criteria for assessing stereo quality in detail, we qualitatively and quantitatively describe both the horizontal resolution and vertical precision of the DTMs. We find that the horizontal resolution of the SOCET SET® DTMs is typically 8–11× the root mean square (RMS) pixel scale of the images, whereas the resolution of the ASP DTMs is 9–13× the maximum pixel scale of the images. We calculate the RMS difference between the ASP and SOCET SET® DTMs as a proxy for the expected vertical precision (EP), which is a function of the matching accuracy and stereo geometry. We consistently find that the matching accuracy is ~0.5 pixels, which is larger than well-established “rules of thumb” that state that the matching accuracy is 0.2–0.3 pixels. The true EP is therefore ~1.7× larger than might otherwise be assumed. In most cases, DTM errors are approximately normally distributed, and errors that are several times the derived EP occur as expected. However, in two DTMs, larger errors (differences) occur and correlate with real topography. These differences primarily result from manual editing of the SOCET SET® DTMs. The product of the DTM error and the resolution is typically 4–8 pixel2 if calculated using the RMS image scale for SOCET SET® DTMs and the maximum images scale for the ASP DTMs, which is consistent with recent work using martian data sets and suggests that the relationship applies more broadly. We evaluate how ASP parameters affect DTM quality and find that using a smaller subpixel refinement kernel results in DTMs with smaller (better) resolution but, in some cases, larger gaps, which are sometimes reduced by increasing the size of the correlation kernel. We conclude that users of ASP should always systematically evaluate the choice of parameters for a given dataset.

We have used a high-precision, high-resolution digital terrain model (DTM) of the NASA Mars 2020 rover Perseverance landing site in Jezero crater based on mosaicked images from the Mars Reconnaissance Orbiter High Resolution Imaging Science Experiment (MRO HiRISE) camera as a reference dataset to evaluate DTMs based on Mars Express High Resolution Stereo Camera (MEX HRSC) and MRO Context camera (CTX) images. Results are consistent with our earlier HRSC-HiRISE comparisons at the Mars Science Laboratory (MSL) Curiosity landing site in Gale crater, confirming that those results were not compromised by the small area compared and potential problems with spatial registration. Specifically, height errors are on the order of half a pixel and correspond to an image matching error of 0.2–0.3 pixel but estimates of horizontal resolution are 10–20 pixels. Products from the HRSC team pipeline at DLR are smoother but more precise vertically than those produced by using the commercial stereo package SOCET SET®. The DLR products are also homogenous in quality, whereas the SOCET products are less smoothed and have higher errors in rougher terrain. Despite this weak variation, our results are consistent with a rule of thumb of 0.2–0.3 pixel matching precision based on many prior studies. Horizontal resolution is significantly coarser than the DTM ground sample distance (GSD), which is typically 3–5 pixels.

AND RESOURCE POTENTIAL FOR LANDED MISSIONS. K. A. Bennett1, L. M. Pigue2, L. Gaddis1, C. C. Allen3, B. T. Greenhagen4, D. A. Paige5, L. Keszthelyi1, L. R. Ostrach1, J. J. Hagerty1, L. A. Edgar1, R. L. Fergason1, J. A. Skinner1. 1USGS Astrogeology Science Center (2255 N Gemini Dr., Flagstaff AZ); 2Northern Arizona University, Flagstaff, AZ; 3NASA Johnson Space Center (retired), Houston, TX; 4Johns Hopkins University Applied Physics Laboratory; 5University of California Los Angeles, Los Angeles CA. (corresponding author email: kbennett@usgs.gov)

Motivation: Geodetically controlled products, including controlled mosaics and Digital Terrain Models (DTMs), provide accurate and consistent basemaps that enable and enhance the science and exploration that could be performed by human crews on the lunar surface and they facilitate communication between engineers and scientists [1]. The use of consistently controlled base products encourages scientific collaborations by aiding strategic planning of data acquisition, supporting the production of geologic maps [2], enabling the accurate and reliable assessment of resources [3,4], and facilitating cross-discipline investigations. A consistent basemap also allows for more accurate integration of data from different instruments, such as visible wavelength images and radar [5,6], and ultimately can maximize the scientific return of lunar science investigations supported and enabled by Artemis. Reliable geodetically controlled products will specifically benefit both Phase 1 and Phase 2 of NASA’s Artemis program. During Phase 1, these consistent and accurate products will enable NASA to safely land human beings on the lunar surface near the Moon’s south pole and facilitate successful operations. These maps also benefit Phase 2, as the same map products should ideally be used both by humans on the lunar surface and by the ground crew and scientists with whom they are communicating to minimize miscommunications and ensure efficient and accurate transfer of vital, potentially life-saving, information. Existing USGS ASC Products: The USGS Astrogeology Science Center (ASC) has produced accurate photogrammetrically corrected mosaics and DTMs using data from the Lunar Reconnaissance Orbiter Camera (LROC) and the Apollo panoramic cameras for the Lunar Mapping Modeling Project (LMMP) [7-9] and as part of research supported by the NASA Lunar Science Institute [NLSI]. In addition, the ASC has developed geodetically controlled LRO MiniRF S-band monostatic radar mosaics of both lunar poles in two look directions, as well as smaller mosaics of Chandrayaan-1 Mini-SAR data [5]. Controlled mosaic for the South Pole and Malapert Massif region: As part of the LMMP effort, we used the Integrated Software for Imagers and Spectrometers (ISIS) [10] software package to create and evaluate control networks and resulting mosaics for the lunar south polar and Malapert Massif region using LROC Narrow Angle Camera (NAC) images (Fig 1). We generated control networks using automatic image-toimage tie point methods and sub-pixel registration (with human oversight) along with bundle adjustment software [10]. These networks were then tied to an illuminated model of Lunar Orbiter Laser Altimeter (LOLA) data. The resulting polar mosaics were orthorectified using gridded LOLA topography, and the Malapert Massif mosaic was orthorectified using the corresponding LROC stereo derived DTM. This methodology resulted in a control network and an orthorectified product that has broad applicability and is tied to the LOLA reference frame.

We compare the thermophysical properties and particle sizes derived from the Mars Science Laboratory rover's Ground Temperature Sensor of the Bagnold dunes, specifically Namib dune, to those derived orbitally from Thermal Emission Imaging System, ultimately linking these measurements to ground truth particle sizes determined from Mars Hand Lens Imager images. In general, we find that all three datasets report consistent particle sizes for the Bagnold dunes (~110–350 μm and are within measurement and model uncertainties), indicating that particle sizes of homogeneous materials inferred from temperature measurements and thermophysical models are reliable. Furthermore, we examine the effects of two physical characteristics that could influence the modeled thermal inertia and particle sizes, including (1) fine‐scale (centimeter to meter scale) ripples and (2) thin layering of indurated/armored materials. To first order, we find that small‐scale ripples and thin (approximately centimeter scale) layers do not significantly affect the determination of bulk thermal inertia from orbital thermal data using a single nighttime temperature. Modeling of a layer of coarse or indurated material reveals that a thin layer (< ~5 mm; similar to what was observed by the Curiosity rover) would not significantly change the observed thermal properties of the surface and would be dominated by the properties of the underlying material. Thermal inertia and particle sizes of relatively homogeneous materials derived from nighttime orbital data should be considered as reliable, as long as there are no significant subpixel anisothermality effects (e.g., lateral mixing of multiple thermophysically distinct materials).

Rocky ejecta craters (RECs) at the Interior Exploration using Seismic Investigations, Geodesy and Heat Transport (InSight) landing site on Elysium Planitia, Mars, provide constraints on crater modification and rates for the Hesperian and Amazonian. The RECs are between 10 m and 1.2 km in diameter and exhibit five classes of preservation. Class 1 represents pristine craters with sharp rims and abundant ejected rocks. From Classes 2 to 5, rims become more subdued, craters are infilled, and the ejecta become discontinuously distributed. High‐Resolution Imaging Science Experiment digital elevation models indicate a maximum depth to diameter ratio of ~0.15, which is lower than pristine models for craters of similar size. The low ratio is related to the presence of a loosely consolidated regolith and early‐stage eolian infill. Rim heights have an average height to diameter ratio of ~0.03 for the most pristine class. The size‐frequency distribution of RECs, plotted using cumulative and differential methods, indicates that crater classes within the diameter range of 200 m to 1.2 km are separated by ~100 to 200 Myr. Smaller craters degrade faster, with classes separated by <100 Myr. Rim erosion can be entirely modeled by nonlinear diffusional processes using the calculated timescales and a constant diffusivity of 8 × 10−7 m2/year for craters 200 to 500 m in diameter. Diffusion models only partly capture depth‐related degradation, which requires eolian infill. Depth degradation and rim erosion rates are 10−2 to 10−3 m/Myr, respectively. The rates are consistent with relatively slow modification that is typical of the last two epochs of Martian history.

Introduction: The third landing site workshop for the 2020 Mars Rover mission was held in February 2017 and reduced the number of candidate landing sites down to three: Columbia Hills (-14.5711°N, 175.4374°E), Jezero Crater (18.4386°N, 77.5031°E), and NE Syrtis Major (17.8899°N, 77.1599°E) [1]. During descent, the vehicle will use terrain relative navigation (TRN) to divert around potential hazards via automated localization onto a pre-made onboard map. To navigate around small hazards, TRN requires a highresolution basemap with minimal distortion and precise image coregistration. Such high precision basemaps will also support mapping of geological units, identification of regions of interest for sample collection, and planning potential traverse routes. Data and Methods: We control higher resolution images to better-controlled lower resolution datasets to remove artificial offset, rotation, and scaling errors. Our underlying control base is the community standard 128 pixel/degree (~462 m sampling) Mars Orbiter Laser Altimeter (MOLA) global topographic basemap [2] and International Astronomical Union’s Mars 2000 coordinate system [3]. For a visible image base, we use 12.5 m/pixel High Resolution Stereo Camera (HRSC) ortho-images [4] that have been corrected for topographic distortions and are well co-registered to MOLA. Stereo images at 6 m/pixel from the Mars Reconnaissance Orbiter (MRO) Context Camera (CTX) [5] have been processed into 20 m elevation posting digital elevation models (DEMs) and 6 m/pixel orthorectified visible images by the USGS [6,7]. Similarly, stereo images from the High-Resolution Imaging Science Experiment (HiRISE) are also processed to produce 1 m elevation posting DEMs and 25 cm/pixel ortho-rectified visible images [8]. We use a geographic information system (GIS), specifically ArcGIS, to create 60-80 tie-points between distinct features in each combination of overlapping fine and coarse resolution images, as well as in overlapping portions of adjacent images with comparable resolutions. Illumination and shadows change between images due to variable lighting geometry, so instead we elected to use the circular outlines of small fresh impact crater rims. We first co-register CTX ortho-images to HRSC, and then co-register HiRISE ortho-images to that CTX. The same horizontal tie-points are also applied to each HiRISE and CTX DEM. In addition to horizontal co-registration, we also perform a vertical correction. During HiRISE DEM generation, HiRISE stereo-derived terrain is roughly tied to the Mars aeroid using MOLA tracks [7], but the sparsity of MOLA tracks often leads to erroneous vertical offsets of up to a few tens of meters at DEM seams. Once we have horizontally controlled the orthoimages and DEMs, we subtract the CTX DEM from each overlapping HiRISE DEM to determine the distribution of any vertical errors. We then fit a plane to the differences using least squares and subtract that fitted offset plane from the HiRISE DEMs to reduce artificial tilts and vertical steps at DEM seams. Results: We have complete HIRISE and CTX DEM and ortho-image coverage for the Jezero crater (Fig. 1) and NE Syrtis (Fig. 2) candidate landing ellipses. We also have complete CTX DEM and orthoimage coverage for Columbia Hills (Fig. 3), as well as several HiRISE DEMs and ortho-images. A strip in the middle of the Columbia Hills ellipse has not yet been processed into a DEM and ortho-images; however, the portion currently lacking HiRISE topography mainly consists of flat and non-hazardous plains, and a nonortho-rectified but map-projected visible HiRISE image may be used for terrain analysis until the DEM is processed.